Recognition of noisy images by PLL networks

We use networks composed of three phase-locked loops (PLLs), where one of them is the master, for recognizing noisy images. The values of the coupling weights among the PLLs control the noise level which does not affect the successful identification of the input image. Analytical results and numerical tests are presented concerning the scheme performance. (c) 2008 Elsevier B.V. All rights reserved.

Multiple synchronous states in static delay-free mutually connected PLL networks

In many engineering applications, the time coordination of geographically separated events is of fundamental importance, as in digital telecommunications and integrated digital circuits. Mutually connected (MC) networks are very good candidates for some new types of application, such as wireless sensor networks. This paper presents a study on the behavior of MC networks of digital phase-locked loops (DPLLs). Analytical results are derived showing that, even for static networks without delays, different synchronous states may exist for the network. An upper bound for the number of such states is also presented. Numerical simulations are used to show the following results: (i) the synchronization precision in MC DPLLs networks; (ii) the existence of synchronous states for the network does not guarantee its achievement and (iii) different synchronous states may be achieved for different initial conditions. These results are important in the neural computation context. as in this case, each synchronous state may be associated to a different analog memory information. (C) 2010 Elsevier B.V. All rights reserved.

The viability of three probiotic organisms grown with yoghurt starter cultures during storage for 21 days at 4 degrees C

This study investigated the viability of probiotic (Lactobacillus acidophilus LA5, Lactobacillus rhamnosus LBA and Bifidobacterium animalis subsp. lactis BL-04) in milk fermented with Lactobacillus delbrueckii subsp. bulgaricus LB340 and Streptococcus thermophilus TAO (yoghurt - Y). Each probiotic strain was grown separately in co-culture with Y and in blends of different combinations. Blends affected fermentation time(s), pH and firmness during storage at 4 degrees C. The product made with Y plus B. animalis subsp. lactis and L. rhamnosus had counts of viable cells at the end of shelf life that met the minimum required to achieve probiotic effect. However, L. acidophilus and L. delbrueckii subsp. bulgaricus were inhibited.

Acquisition of the English article system in SLA and the Missing Surface Inflection Hypothesis

This paper examines the article system in interlanguage grammar focusing on Japanese learners of English, whose native language lacks articles. It will be demonstrated that for the acquisition of the English article system, count/mass distinctions and definiteness are the crucial factors. Although Japanese does not employ the article system to encode these aspects, it will be argued that they are nevertheless syntactically encoded through its classifier system. Hence, the problem for these learners must be to map these features onto the appropriate surface forms as the Missing Surface Inflection Hypothesis predicts (Prévost & White 2000). This suggestion will further be supported empirically by a fill-in-the article task. It will be concluded that these Japanese learners understand the English article system fairly well, possibly due to their native language, yet have problems with realizing the relevant features (i.e. count/mass distinctions and definiteness) in the target language.

Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Calcium-permeable AMPA receptors mediate long-term potentiation in interneurons in the amygdala

Fear conditioning is a paradigm that has been used as a model for emotional learning in animals'. The cellular correlate of fear conditioning is thought to be associative N-methyl-D-aspartate (NMDA) receptor-dependent synaptic plasticity within the amygdala(1-3). Here we show that glutamatergic synaptic transmission to inhibitory interneurons in the basolateral amygdala is mediated solely by alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors. In contrast to AMPA receptors at inputs to pyramidal neurons, these receptors have an inwardly rectifying current-voltage relationship, indicative of a high permeability to calcium(4 5), Tetanic stimulation of inputs to interneurons caused an immediate and sustained increase in the efficacy of these synapses. This potentiation required a rise in postsynaptic calcium, but was independent of NMDA receptor activation. The potentiation of excitatory inputs to interneurons was reflected as an increase in the amplitude of the GABAA-mediated inhibitory synaptic current in pyramidal neurons. These results demonstrate that excitatory synapses onto interneurons within a fear conditioning circuit show NMDA-receptor independent long-term potentiation. This plasticity might underlie the increased synchronization of activity between neurons in the basolateral amygdala after fear conditioning(6).

Mechanisms of substitution reactions on cyclometallated platinum(IV) complexes: "Quasi-labile" systems

The substitution reactions of SMe2 by phosphines (PMePh2, PEtPh2, PPh3, P(4-MeC6H4)(3), P(3-MeC6H4)(3), PCy3) on Pt-IV complexes having a cyclometalated imine ligand, two methyl groups in a cis-geometrical arrangement, a halogen, and a dimethyl sulfide as ligands, [Pt(CN)(CH3)(2)(X)(SMe2)], have been studied as a function of temperature, solvent, and electronic and steric characteristics of the phosphines and the X and CN ligands. In all cases, a limiting dissociative mechanism has been found, where the dissociation of the SMe2 ligand corresponds to the rate-determining step. The pentacoordinated species formed behaves as a true pentacoordinated Pt-IV compound in a steady-state concentration, given the solvent independence of the rate constant. The X-ray crystal structures of two of the dimethyl sulfide complexes and a derivative of the pentacoordinate intermediate have been determined. Differences in the individual rate constants for the entrance of the phosphine ligand can only be estimated as reactivity ratios. In all cases an effect of the phosphine size is detected, indicating that an associative step takes place from the pentacoordinated intermediate. The nature of the (CN) imine and X ligands produces differences in the dimethyl sulfide dissociation reactions rates, which can be quantified by the corresponding DeltaS double dagger values (72, 64, 48, 31, and 78 J K-1 mol(-1) for CN/X being C6H4CHNCH2C6H5/Br, C6H4CHNCH2-(2,4,6-(CH3)(3))C6H2/Br, C6H4CHNCH2C6H5/Cl, C6Cl4CHNCH2C6H5/Cl, and C6W4CH2NCHC6H5/ Pr, respectively). As a whole, the donor character of the coordinated C-aromatic and X atoms have the greatest influence on the dissociativeness of the rate-determining step.

A context noise model of episodic word recognition

Item noise models of recognition assert that interference at retrieval is generated by the words from the study list. Context noise models of recognition assert that interference at retrieval is generated by the contexts in which the test word has appeared. The authors introduce the bind cue decide model of episodic memory, a Bayesian context noise model, and demonstrate how it can account for data from the item noise and dual-processing approaches to recognition memory. From the item noise perspective, list strength and list length effects, the mirror effect for word frequency and concreteness, and the effects of the similarity of other words in a list are considered. From the dual-processing perspective, process dissociation data on the effects of length, temporal separation of lists, strength, and diagnosticity of context are examined. The authors conclude that the context noise approach to recognition is a viable alternative to existing approaches.

The game to play: expanding the co-opetition proposal through the strategic games matrix

Purpose - Using Brandenburger and Nalebuff`s 1995 co-opetition model as a reference, the purpose of this paper is to seek to develop a tool that, based on the tenets of classical game theory, would enable scholars and managers to identify which games may be played in response to the different conflict of interest situations faced by companies in their business environments. Design/methodology/approach - The literature on game theory and business strategy are reviewed and a conceptual model, the strategic games matrix (SGM), is developed. Two novel games are described and modeled. Findings - The co-opetition model is not sufficient to realistically represent most of the conflict of interest situations faced by companies. It seeks to address this problem through development of the SGM, which expands upon Brandenburger and Nalebuff`s model by providing a broader perspective, through incorporation of an additional dimension (power ratio between players) and three novel, respectively, (rival, individualistic, and associative). Practical implications - This proposed model, based on the concepts of game theory, should be used to train decision- and policy-makers to better understand, interpret and formulate conflict management strategies. Originality/value - A practical and original tool to use game models in conflict of interest situations is generated. Basic classical games, such as Nash, Stackelberg, Pareto, and Minimax, are mapped on the SGM to suggest in which situations they Could be useful. Two innovative games are described to fit four different types of conflict situations that so far have no corresponding game in the literature. A test application of the SGM to a classic Intel Corporation strategic management case, in the complex personal computer industry, shows that the proposed method is able to describe, to interpret, to analyze, and to prescribe optimal competitive and/or cooperative strategies for each conflict of interest situation.

Startle-potentiation during nonaversive human conditioning

Fear-potentiated startle is a well-established measure of emotional learning in nonhuman animals. In humans, startle potentiation in anticipation of an aversive unconditional stimulus (US) has been interpreted as reflecting the same emotional process. This interpretation was supported by previous failures to fmd startle potentiation in anticipation of nonaversive USs, reactiontime tasks. The present research questions these results. Experiment 1 found startle-potentiation in anticipation of an aversive US, which resulted in increased dislike of the conditional stimulus (CS), and in anticipation of a nonaversive US, which did not affect CS valence. Experiment 2 replicated the latter finding, indicating that provision of performance feedback enhanced the salience of the reaction time task USs and thus anticipatory startle potentiation. The present results pose problems for the interpretation of fmdings of potentiated startle in human-aversive conditioning as reflecting emotion. Rather, startle potentiation during aversive and non-aversive conditioning may reflect the attentional processes known to occur during human-associative learning.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Incidental Encoding Strategies Did Not Improve Contextual Memory in Parkinson`s Disease Patients

Background. This study investigated the performance of patients with idiopathic Parkinson`s disease (PD) without dementia for incidental recognition memory and the effect of encoding strategies on contextual memory. Methods. The authors studied 21 patients with PD (ages 60-85, 12 women; Hoehn and Yahr I-III, Activities of Daily Living 70%-100%) and 22 healthy controls (ages 60-84, 18 women). Participants completed the vocabulary subtest of the Wechsler Adult Intelligence Scale and the Wisconsin Card Sorting Test (WCST). To assess the incidental recognition memory for item (object) and context (location of the object), participants of each group were assigned to 1 of 2 encoding conditions: (a) an incidental associative instruction to bind the object to its location or (b) a nonassociative, nonspecific instruction. Results. PD patients showed performance comparable to the control group`s on the vocabulary subtest and WCST. In contrast to controls, PD patients were unable to take advantage of the associative encoding instruction, which also had a deleterious effect on item recognition. Conclusion. This sample of participants with PD showed diminished item and context recognition memory and an impaired ability to use incidental memory encoding strategy, suggesting a compromised cognitive reserve. The fact that these alterations occurred in early stages of PD, and prior to more general cognitive alterations such as executive dysfunction, should be considered in the management of patients by using specific cognitive rehabilitation interventions.

Fear of heights: cognitive performance and postural control

Fear of heights, or acrophobia, is one of the most frequent subtypes of specific phobia frequently associated to depression and other anxiety disorders. Previous evidence suggests a correlation between acrophobia and abnormalities in balance control, particularly involving the use of visual information to keep postural stability. This study investigates the hypotheses that (1) abnormalities in balance control are more frequent in individuals with acrophobia even when not exposed to heights, that (2) acrophobic symptoms are associated to abnormalities in visual perception of movement; and that (3) individuals with acrophobia are more sensitive to balance-cognition interactions. Thirty-one individuals with specific phobia of heights and thirty one non-phobic controls were compared using dynamic posturography and a manual tracking task. Acrophobics had poorer performance in both tasks, especially when carried out simultaneously. Previously described interference between posture control and cognitive activity seems to play a major role in these individuals. The presence of physiologic abnormalities is compatible with the hypothesis of a non-associative acquisition of fear of heights, i.e., not associated to previous traumatic events or other learning experiences. Clinically, this preliminary study corroborates the hypothesis that vestibular physical therapy can be particularly useful in treating individuals with fear of heights.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.